|
|
Absolute deviation, 绝对离差
2 y; G# R- ~9 t5 hAbsolute number, 绝对数
2 p; e3 e, b8 l* K) y4 e: n% mAbsolute residuals, 绝对残差
9 Q3 i1 I: |/ @! _6 [Acceleration array, 加速度立体阵: h7 d) t Y8 i
Acceleration in an arbitrary direction, 任意方向上的加速度
+ h& Q3 u2 Y! F+ b- q# I" d5 iAcceleration normal, 法向加速度4 M: Q. l! _: s+ e
Acceleration space dimension, 加速度空间的维数
+ q. L( X" i/ P2 V% Y; XAcceleration tangential, 切向加速度+ F. Q) ~* g# X2 }, t* |1 Z( i; a
Acceleration vector, 加速度向量
/ T4 r O- _0 |9 R3 s J( yAcceptable hypothesis, 可接受假设1 d6 W6 n. A2 g; r& B! e
Accumulation, 累积
; L3 X3 G4 P" F( |# d- ZAccuracy, 准确度" y$ c) V1 n! u# i0 X8 o. z
Actual frequency, 实际频数
1 r! w( i b5 tAdaptive estimator, 自适应估计量+ x$ I5 Y2 U# R% ]- |
Addition, 相加
" C4 t& Z; X: v) F5 |Addition theorem, 加法定理
7 {& e1 D% s0 n' T" AAdditivity, 可加性' H9 i) d/ r7 @) B+ d( H6 V
Adjusted rate, 调整率' V& P- l0 O' q6 G; `4 z( b. {: j
Adjusted value, 校正值
: @3 i1 C \* W$ i; OAdmissible error, 容许误差
9 _5 }8 I/ @# V& G2 jAggregation, 聚集性8 }0 F; V0 n! ~
Alternative hypothesis, 备择假设* L4 |2 V. H+ l% n1 v
Among groups, 组间
$ O; z' A2 G+ n/ g1 x. ]( iAmounts, 总量
; Q- }% s' U6 Z, Z/ k) Z9 b. TAnalysis of correlation, 相关分析
5 G. ?. `2 A! ^Analysis of covariance, 协方差分析
. l: Z* S/ d; A9 jAnalysis of regression, 回归分析7 z1 a: {' J6 _0 r
Analysis of time series, 时间序列分析' b8 _# H; F9 L& \6 b+ x. n
Analysis of variance, 方差分析
* ~( Q1 _5 h w8 C2 CAngular transformation, 角转换
V% d8 [" a8 l6 u3 [ANOVA （analysis of variance）, 方差分析$ [2 Y) j/ q( r# z8 J3 I: g- Z
ANOVA Models, 方差分析模型
) Y ?1 y3 a. c5 R, g8 kArcing, 弧/弧旋) k' J. | u3 L6 ?# F# [- `
Arcsine transformation, 反正弦变换3 T5 ]: L! R h( X; ?
Area under the curve, 曲线面积- ?! U/ t2 Q6 G4 L
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
: Q( P" f4 w# W: g* G6 R; ~; E; JARIMA, 季节和非季节性单变量模型的极大似然估计 % Y% a/ c1 Q' Z1 @5 x
Arithmetic grid paper, 算术格纸! O7 ~$ j, s( J& F" W( X0 _. y( B
Arithmetic mean, 算术平均数
, h4 E0 ~, M. f+ `Arrhenius relation, 艾恩尼斯关系0 C1 S3 k- v0 G3 v, S& e# D
Assessing fit, 拟合的评估
4 N/ s( t1 M0 Y8 o) B& u* {, JAssociative laws, 结合律
, D, S& |# m% I4 v/ ?; JAsymmetric distribution, 非对称分布1 k D: ? E" K8 K, t& @
Asymptotic bias, 渐近偏倚
( p! p6 g$ ~1 g6 q5 e$ p3 mAsymptotic efficiency, 渐近效率8 Z9 z9 X/ N2 w
Asymptotic variance, 渐近方差# {% }7 ?8 l2 p# @& Z
Attributable risk, 归因危险度
% h: ]+ k, i8 k$ M" xAttribute data, 属性资料5 ~+ x' K$ ]( T4 m
Attribution, 属性
7 a$ l& e( w% b5 c6 z5 M$ CAutocorrelation, 自相关
/ }0 q, x: T( ~9 v( T( rAutocorrelation of residuals, 残差的自相关' R! L% m& g- Z1 D
Average, 平均数
: v* L' K5 c% \2 L( \Average confidence interval length, 平均置信区间长度
' p9 Q3 X& z, }& Z# j5 _Average growth rate, 平均增长率$ y1 Q+ r" G4 H0 D1 a* H1 p! e5 P
Bar chart, 条形图$ k3 I3 d3 y' y( ^+ u. M% M+ ^4 \8 R
Bar graph, 条形图
( g/ ~, U1 S! t% _' mBase period, 基期
" m N5 A! q2 o/ x* ABayes' theorem , Bayes定理4 E; p v9 o+ o+ e7 G
Bell-shaped curve, 钟形曲线
" L: g. @' ~% ^% D3 z; tBernoulli distribution, 伯努力分布
9 o2 A& {/ {& m& r! D% T% q3 XBest-trim estimator, 最好切尾估计量
0 ~8 R; n. }* h! [0 {8 w# w% bBias, 偏性
. }, |5 B* f' j* q( {Binary logistic regression, 二元逻辑斯蒂回归$ x6 E5 ^* w, o/ w6 h5 G" N
Binomial distribution, 二项分布/ E/ y5 M1 \0 ^2 k
Bisquare, 双平方
& o4 R- A0 J* \3 m" L* p" oBivariate Correlate, 二变量相关2 G* z4 ^' o6 s0 t9 Q
Bivariate normal distribution, 双变量正态分布
& _3 x0 a& p2 Y p3 K; s0 Z MBivariate normal population, 双变量正态总体6 k. c9 Y+ `$ t1 I4 U# @
Biweight interval, 双权区间$ g, t9 Y9 M8 J# Q5 t' w
Biweight M-estimator, 双权M估计量
H, o- N. {- L/ \- V/ iBlock, 区组/配伍组 q. {. C4 E1 q$ M! U8 v* {
BMDP(Biomedical computer programs), BMDP统计软件包
) b: Q/ h# R |6 V# |Boxplots, 箱线图/箱尾图+ u5 E+ N& V9 p
Breakdown bound, 崩溃界/崩溃点: ~1 @2 T) V8 d
Canonical correlation, 典型相关
6 ?5 M' y8 y& D2 mCaption, 纵标目
4 a2 [$ f5 X# C( yCase-control study, 病例对照研究+ m" Q& Z2 W5 C$ Q' N, w
Categorical variable, 分类变量
+ \! M3 n) @6 a9 v; RCatenary, 悬链线
7 {1 w" q" O" {2 G$ H1 uCauchy distribution, 柯西分布
' Z! K' n0 g. c& FCause-and-effect relationship, 因果关系7 h0 y) f4 W" s" L
Cell, 单元6 w; i# m1 X$ m* S
Censoring, 终检1 ~! V y) J8 p5 T3 H& m; X) E, R
Center of symmetry, 对称中心7 J0 R, U$ Q1 Z; D
Centering and scaling, 中心化和定标
+ g3 r' x1 u. l; XCentral tendency, 集中趋势3 V0 V7 B) g& @
Central value, 中心值; o# H4 X6 [8 P/ h9 e& d6 K
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测; ~$ t/ M8 _" z, s* s" r! y
Chance, 机遇1 L7 X3 G( Q0 L V
Chance error, 随机误差
4 k6 D: r( I$ _6 wChance variable, 随机变量6 Q, Z* {9 I9 h2 Y
Characteristic equation, 特征方程9 C8 V& C$ u( o& P! U" L. ?% R
Characteristic root, 特征根
: S N1 ~9 g2 i" o) I% @+ LCharacteristic vector, 特征向量 [+ m6 l* j7 Z0 k) y
Chebshev criterion of fit, 拟合的切比雪夫准则
& V! S$ H" \6 q3 ]2 iChernoff faces, 切尔诺夫脸谱图
4 n8 `3 T( s6 U, \' ?: ?Chi-square test, 卡方检验/χ2检验
- h0 r$ T4 g! _0 T+ g& a* kCholeskey decomposition, 乔洛斯基分解. l' Q( c- E* p$ ^9 i0 n2 ~
Circle chart, 圆图 ' _, g0 K" [2 q% |5 V
Class interval, 组距
8 c0 @8 ~0 ^+ O9 Z% S- I' [8 z/ tClass mid-value, 组中值
+ b9 g& s& a. L8 P- ~/ ^1 D" C2 tClass upper limit, 组上限
% A7 L, i4 @+ X4 Q) g8 ~Classified variable, 分类变量
5 _( n- d1 D9 s) I# H: Z( C0 @Cluster analysis, 聚类分析" G/ `5 U+ M- D* S( _8 [) X
Cluster sampling, 整群抽样
' q% \: ]) E) H' w; }& UCode, 代码5 E# u- f. l) {' e, ^+ x! k
Coded data, 编码数据
4 E4 {. o% P. NCoding, 编码' N" o% A2 C" K
Coefficient of contingency, 列联系数* j( E# g1 v5 q8 Y R
Coefficient of determination, 决定系数: D# f$ q. @: \, L7 a0 \
Coefficient of multiple correlation, 多重相关系数
+ R' R0 z M8 k6 G. c3 a+ xCoefficient of partial correlation, 偏相关系数
. D0 V# }) _ i! q F& O: i& NCoefficient of production-moment correlation, 积差相关系数
$ {$ p6 D$ Y: E3 F: ?Coefficient of rank correlation, 等级相关系数' j* w# m) u) j9 o
Coefficient of regression, 回归系数, v+ B; A7 o* u+ o3 E# c
Coefficient of skewness, 偏度系数
: A+ F8 O- Z( l: R wCoefficient of variation, 变异系数
' P6 N/ F0 b6 W; cCohort study, 队列研究0 f( a( i* { N9 z5 \. h6 W1 p
Column, 列8 E- ?- `: ~ O8 E% @! d! q' A
Column effect, 列效应9 D8 k. ]5 l' o* ]' V0 Y; ~
Column factor, 列因素3 T9 x2 U- J5 p7 t
Combination pool, 合并- M" X: ~2 T; a) Z" \! w+ D
Combinative table, 组合表
# g; |3 w; U7 Z- f+ @! z) R! mCommon factor, 共性因子7 c4 M" j) k- V5 A! G5 S
Common regression coefficient, 公共回归系数9 c% S% g& A+ d, y; i# {
Common value, 共同值9 f& |: P" H, U6 L* h7 f
Common variance, 公共方差
- y; w, k D K9 j3 J3 ^7 q @Common variation, 公共变异& G$ N0 S: o% ^! @* f7 |+ E
Communality variance, 共性方差
3 D* L X' ^+ J, p9 EComparability, 可比性$ e1 [7 U: Z# k4 f
Comparison of bathes, 批比较8 P7 V5 _# {# o! e% R0 m
Comparison value, 比较值# J4 S" ]! [7 x) \3 |' E
Compartment model, 分部模型
R( W, i9 ]% _! ?6 |5 x' G% [Compassion, 伸缩7 G$ n+ {/ @ ~, I9 J% ]1 `
Complement of an event, 补事件
3 H q& q% x+ ^1 I2 ^Complete association, 完全正相关
4 ~/ G" k6 w- Z" EComplete dissociation, 完全不相关
U& b9 G; \& nComplete statistics, 完备统计量
0 J! s& ]7 r9 y9 lCompletely randomized design, 完全随机化设计
% X4 m" `$ V. P8 n% GComposite event, 联合事件: c& ^( e8 a- e9 G+ P2 M/ L) n+ {
Composite events, 复合事件' z& ^5 L/ g5 a
Concavity, 凹性
1 }$ p: Q! b7 Q. k& e) hConditional expectation, 条件期望8 F* P+ f# U1 V/ e% s( {' \( G
Conditional likelihood, 条件似然
7 m1 e* e+ q" m9 i6 s2 f, x& NConditional probability, 条件概率
L) X, H& J; _, R4 E1 UConditionally linear, 依条件线性
+ ^9 T, l6 Q$ P& D: @Confidence interval, 置信区间. @' p& J, M4 x# w* v
Confidence limit, 置信限& ]$ K; e! n# f. y& k+ A
Confidence lower limit, 置信下限
# c" M9 U, N2 \" q' I- i( bConfidence upper limit, 置信上限
0 Z- s3 \. u! p" NConfirmatory Factor Analysis , 验证性因子分析. p/ q: c. Q+ `# ?7 X
Confirmatory research, 证实性实验研究! Y E! E7 Y, I* n- n
Confounding factor, 混杂因素
7 X7 |. l9 o- s' O. m( S3 P# KConjoint, 联合分析/ O$ N. {2 k- B6 N
Consistency, 相合性. J' D, Q: w% P' J
Consistency check, 一致性检验
c7 ~- P2 K& [Consistent asymptotically normal estimate, 相合渐近正态估计
( W& u4 e: G# N$ SConsistent estimate, 相合估计; N$ E% \+ [, r: C# P3 E
Constrained nonlinear regression, 受约束非线性回归
$ q7 h5 X: q- n, R8 P% l$ m! gConstraint, 约束- A- J2 U" s, B! u2 ^
Contaminated distribution, 污染分布
, P ]+ |3 ~7 q! ?4 nContaminated Gausssian, 污染高斯分布$ z4 ^2 O) Z" h! O# ?3 U5 e4 \8 u
Contaminated normal distribution, 污染正态分布
* n1 h! q5 q h. B6 r3 F+ B! G; aContamination, 污染% }3 o2 Q7 t& v. B5 ~, R
Contamination model, 污染模型
8 r% i9 |9 ~& l2 f2 A: ]# n4 SContingency table, 列联表/ v4 ]( N3 ?, Z+ P2 A
Contour, 边界线
0 D' M$ P ]* P9 k+ v% }Contribution rate, 贡献率9 [1 f" }7 b' M
Control, 对照
' W6 x4 P7 Z+ J+ v ?Controlled experiments, 对照实验
& e6 F k) x5 @ ], w! v7 a( oConventional depth, 常规深度# K/ l' t3 I6 t7 U( g; g$ z0 r6 j
Convolution, 卷积! p/ [0 U- Y% Y" _- I4 v8 \
Corrected factor, 校正因子
: }5 O7 w e7 [3 b: NCorrected mean, 校正均值4 T5 p4 y. ]: d8 E5 H' [
Correction coefficient, 校正系数
% _7 C" `9 o- |. g/ `7 u1 qCorrectness, 正确性5 { q6 c% ?$ ?" |4 A$ b! K' A
Correlation coefficient, 相关系数
1 n$ ?0 M6 |5 L' r: ?, v( W; PCorrelation index, 相关指数5 _& N, { q6 J( N' H: l5 ~6 ^
Correspondence, 对应1 Y5 Z |/ `2 a) d, z
Counting, 计数3 u Q; l; |. i, l2 t) y6 B
Counts, 计数/频数
4 n z4 `3 H8 {& p7 I1 n! B; BCovariance, 协方差3 |6 _, T5 O r# Q
Covariant, 共变 - @2 v0 {1 ?- g: e- R! z. |
Cox Regression, Cox回归9 |* \( b& X4 C* z l+ m
Criteria for fitting, 拟合准则
7 f! V2 D( C0 K- i" i3 wCriteria of least squares, 最小二乘准则6 ]: d) U. g2 }: g9 Y, c) k" l, r
Critical ratio, 临界比) ~: C! E8 |8 B; d" r
Critical region, 拒绝域, U. z, x: r( P
Critical value, 临界值9 E/ _0 ] C+ t4 L
Cross-over design, 交叉设计7 t7 j# u. O" z
Cross-section analysis, 横断面分析
% g& E9 X9 ~7 HCross-section survey, 横断面调查
) T" I0 g. d% Z- d) I& F" }Crosstabs , 交叉表
* T5 C) [7 g; A! y3 y. iCross-tabulation table, 复合表. X2 p* Y7 [7 {/ l( @4 ?
Cube root, 立方根
' P2 c! L6 @: SCumulative distribution function, 分布函数: P- a1 ^: ?2 h, x/ H- W3 g8 `) I
Cumulative probability, 累计概率
3 O+ G# m; ?6 `% g- n3 v' ]Curvature, 曲率/弯曲
, s+ w- H3 o" V* _1 xCurvature, 曲率
; Z2 n, R8 `, p2 PCurve fit , 曲线拟和
+ h# c; Z& \7 R) I A" XCurve fitting, 曲线拟合+ \: I" O8 S V4 q( s
Curvilinear regression, 曲线回归* K& t3 M6 G' H/ U b: }
Curvilinear relation, 曲线关系
& S* G1 H% a! d" Q7 a( LCut-and-try method, 尝试法
4 }6 q8 P2 w" d* dCycle, 周期 |- @! v. w( h" _4 q
Cyclist, 周期性
" t O/ h3 V+ `( X! Z- lD test, D检验, G. q' f M" d) q
Data acquisition, 资料收集
; K( ~% A8 V. }% C; i5 XData bank, 数据库
7 p) j6 V2 J2 ~9 yData capacity, 数据容量
7 f) N6 r7 n; a. W% gData deficiencies, 数据缺乏
, ?# D0 L5 H FData handling, 数据处理! u& G1 h0 [" {
Data manipulation, 数据处理
1 \/ t1 {8 y7 A3 l0 wData processing, 数据处理" _2 P+ L) `6 C7 J
Data reduction, 数据缩减) w3 h- ~: t' W8 |! h
Data set, 数据集9 w8 X& P: C5 s, ?: `( S
Data sources, 数据来源% B9 q9 V, S: F" w5 ?# ^
Data transformation, 数据变换0 M6 } x: w* _5 I2 Y7 c F2 o! b. n3 j
Data validity, 数据有效性! E B" s2 p7 ^
Data-in, 数据输入
* D% J! [9 ^; A* G5 ^, j- sData-out, 数据输出
0 _& P. ^. k* H/ l6 }3 WDead time, 停滞期
5 s9 Q7 n$ ?2 {% D( M7 a# m! dDegree of freedom, 自由度% F( |6 S* Q' }, ~7 X1 T; b
Degree of precision, 精密度
+ H4 V0 t0 L2 m4 l& X- }Degree of reliability, 可靠性程度/ B8 ~/ m1 e6 U) N& V2 \3 R0 n
Degression, 递减% p4 \3 A7 K# s
Density function, 密度函数
: x0 O5 ^; G5 m/ p3 G/ WDensity of data points, 数据点的密度5 v" ^! {' j6 p" g4 _
Dependent variable, 应变量/依变量/因变量
' N6 J+ B' J. W) I: b( EDependent variable, 因变量! U. v7 p4 l" {( j6 @- Z
Depth, 深度; R- N; C. S; b2 ~( ~3 k4 A; j3 x
Derivative matrix, 导数矩阵4 S/ X, D* X1 L! X+ _
Derivative-free methods, 无导数方法% w! f$ V1 h2 j* ^5 C# O3 i
Design, 设计, j N5 O' o h. t* G9 R& q
Determinacy, 确定性
- N; g9 K& q+ P4 mDeterminant, 行列式
5 Z: r7 E& V* x9 d. |Determinant, 决定因素& [& K+ @5 j2 W: b+ } \
Deviation, 离差2 F7 n( M8 Z( ]4 l3 b U o
Deviation from average, 离均差
, l. e2 N$ j1 X. G) ADiagnostic plot, 诊断图
7 {/ F" x4 M5 c1 E# ^7 n% M1 p& fDichotomous variable, 二分变量# h5 C9 h, z+ j7 A8 W5 a
Differential equation, 微分方程7 b5 f6 q2 a9 w# o) \
Direct standardization, 直接标准化法2 p% D1 C/ k- S7 C9 o
Discrete variable, 离散型变量3 `( \+ S: z& s7 g8 s; d6 y2 o1 p
DISCRIMINANT, 判断 0 N+ D8 a8 m2 p
Discriminant analysis, 判别分析9 h; f- |4 p. v( T# m' C# D: v
Discriminant coefficient, 判别系数
; t* y( ^' [1 d* q, s, N8 tDiscriminant function, 判别值& B/ A8 u! ?8 n/ q- G2 i
Dispersion, 散布/分散度3 y) b! l. ]6 }4 y) Q
Disproportional, 不成比例的
- K$ @: _. f h+ t: KDisproportionate sub-class numbers, 不成比例次级组含量
9 U$ p, \2 M2 C/ r$ j d' V }Distribution free, 分布无关性/免分布
& K W* |; Q r! T9 oDistribution shape, 分布形状+ O2 u/ U5 \* u
Distribution-free method, 任意分布法4 m b/ R$ r7 M p
Distributive laws, 分配律7 ?6 t) W$ u6 i- A2 C$ P1 g
Disturbance, 随机扰动项
; f4 y' z6 I- O! C+ a, \3 ?* C9 CDose response curve, 剂量反应曲线9 k1 ^0 ]! q) v8 t, H; {. ?
Double blind method, 双盲法) z& S; O" V. U! p1 ]& g
Double blind trial, 双盲试验
3 U) F* x& O$ t1 n q' fDouble exponential distribution, 双指数分布
^1 n4 e0 ~ k; cDouble logarithmic, 双对数
# P+ \- g5 L! s: ]+ F7 |+ L+ gDownward rank, 降秩9 I! k( z6 {+ V& R" n7 f
Dual-space plot, 对偶空间图
/ o' u, T1 ?! M- K& `/ H/ LDUD, 无导数方法
+ ?! `+ l4 W& n' o% JDuncan's new multiple range method, 新复极差法/Duncan新法
5 c5 k* u' |( EEffect, 实验效应
/ z% Q y8 [4 e. q( _. j, M9 l) d3 lEigenvalue, 特征值
8 b" p* C# s# y$ d7 HEigenvector, 特征向量
- | p3 v! ?6 E0 X. d. ]1 vEllipse, 椭圆
7 m! c# @& u2 F' ]5 N5 D; pEmpirical distribution, 经验分布
5 t z- ?( I' c1 P2 R. bEmpirical probability, 经验概率单位6 Z' i2 V0 K1 m; H# c0 J* a- o
Enumeration data, 计数资料
1 O0 g2 D4 h8 |: Y5 Q1 IEqual sun-class number, 相等次级组含量$ J9 a$ c0 t2 ?; i% d1 u( V- g. ~
Equally likely, 等可能) T7 n6 Z b: p
Equivariance, 同变性& o. d! `" [7 j D, @$ b: l
Error, 误差/错误
2 B+ c! _/ ?' ~0 _' D7 l* RError of estimate, 估计误差
R' m% |/ E0 UError type I, 第一类错误; c% @( c' V9 V6 L8 i. [8 Y/ p* T( P
Error type II, 第二类错误* a+ ?# w w8 X5 B3 p: E
Estimand, 被估量: ?: S; ?3 {/ a. u$ k3 O% T( S
Estimated error mean squares, 估计误差均方
% J$ A# k; X) ]; @6 AEstimated error sum of squares, 估计误差平方和
1 d$ X1 ^1 X0 w) f9 l4 K2 G) M" gEuclidean distance, 欧式距离
0 A! z& B/ B# N0 z' X5 o1 Z; ]Event, 事件$ O# N% j$ k- ]% t* N1 O" O& f9 m" M, b
Event, 事件
. Q& h1 e$ F) _3 @2 h3 O8 qExceptional data point, 异常数据点: O, B3 s, _' ^# Y3 R2 q+ Y+ O
Expectation plane, 期望平面5 @$ f4 i4 ~9 q1 U% s: B( f
Expectation surface, 期望曲面& J1 K9 |% ^' C1 b' t
Expected values, 期望值
$ \5 S; D# g TExperiment, 实验
. s$ M8 ^" [/ V3 ^- X0 j2 {5 D5 aExperimental sampling, 试验抽样
a7 ?/ T5 e8 m2 o. C4 BExperimental unit, 试验单位
# [0 A. u; O1 hExplanatory variable, 说明变量
& e4 ]) ?6 ~- i$ d% w- ?Exploratory data analysis, 探索性数据分析
5 v+ s2 y8 ^# S# Z& r% pExplore Summarize, 探索-摘要8 Q+ r# _: }, G1 ~- n
Exponential curve, 指数曲线
" t; C: Q* B& Q3 G, r* m( uExponential growth, 指数式增长
4 F, S' A$ T8 C0 C3 K4 UEXSMOOTH, 指数平滑方法 . k& G( Y& h6 u! N' E% i
Extended fit, 扩充拟合5 _! F. u" x) ]2 H3 u* C( p
Extra parameter, 附加参数6 V; ]: b) C G# [+ Y0 s
Extrapolation, 外推法
8 N1 C0 A6 e; mExtreme observation, 末端观测值" o1 ?* }/ ]6 H! U& W
Extremes, 极端值/极值! j& e- U0 Q+ E) z, K; Y; P/ g
F distribution, F分布/ a9 n2 A- n8 _# `( D" u
F test, F检验8 S" g* n2 [) O3 w+ v4 H0 o- { q5 b9 r
Factor, 因素/因子
F6 ^& E( w( K% ~1 ?Factor analysis, 因子分析; ^8 m- R0 Y1 d" {9 ?# _( n+ i
Factor Analysis, 因子分析1 L+ K" C+ f9 \1 t
Factor score, 因子得分
5 U. H( I6 a3 T* C0 ?- qFactorial, 阶乘
6 X$ }" K4 X" ^6 W$ w, C8 ]Factorial design, 析因试验设计
2 K0 w7 e t9 D9 `! Z P" TFalse negative, 假阴性
" M$ l& e; i8 W1 FFalse negative error, 假阴性错误
# b& o: |1 \# x5 m U. `8 ?Family of distributions, 分布族/ w8 W4 A" d1 {% V8 ^" k
Family of estimators, 估计量族
2 _( y3 i+ [! D p5 R- |7 @Fanning, 扇面
, F r$ V" o+ Z' p- LFatality rate, 病死率
$ \! O+ v' i) ]Field investigation, 现场调查
) t1 _1 H9 F0 r0 s* jField survey, 现场调查
9 Z* E! ^! j: ZFinite population, 有限总体
0 ^2 G5 g" J* g$ j, V n; W2 [( M3 qFinite-sample, 有限样本) m8 s8 E( e2 l3 `( c& }
First derivative, 一阶导数
' X( a5 ?' t' y3 oFirst principal component, 第一主成分7 v! {: k- l/ F) l1 d
First quartile, 第一四分位数
$ Z9 G) K; o5 k1 b0 C7 AFisher information, 费雪信息量
% P, d2 w. T( }+ u s4 gFitted value, 拟合值3 L5 ]2 m* T6 b" w% {+ Q
Fitting a curve, 曲线拟合
9 f( c9 _# h9 G$ \Fixed base, 定基
! H2 o4 E; A' I! \, v+ \Fluctuation, 随机起伏# _- f0 b k% |* }' z0 s
Forecast, 预测% q+ a* z) s& M4 u7 e) M
Four fold table, 四格表5 R! k1 t' n- e& T4 J
Fourth, 四分点6 D; L( R! a) D. ?' a8 U$ w; T
Fraction blow, 左侧比率1 o3 t2 F& V( _, W; ]7 d* u
Fractional error, 相对误差
4 R1 c( `% r- N" [/ W4 FFrequency, 频率: |# Q& v' u$ G; d I' ^& y
Frequency polygon, 频数多边图! o9 G4 N8 A3 u6 ^1 l+ n3 v' o! f3 a
Frontier point, 界限点/ r7 [$ [0 w- i- ^
Function relationship, 泛函关系# J: }7 j, F( N1 D0 L
Gamma distribution, 伽玛分布
, F1 Q0 _1 n( ? BGauss increment, 高斯增量, X6 Y! g: X. ?# B9 u
Gaussian distribution, 高斯分布/正态分布, H, n4 F# P* ]9 {: b, v( [0 T) E
Gauss-Newton increment, 高斯-牛顿增量& j; H) O% H( |' u. a
General census, 全面普查' [$ h% W/ O( J: g6 b7 X9 ^4 m. {
GENLOG (Generalized liner models), 广义线性模型
% K* b& A4 W$ W0 Q* F) z& F% l6 aGeometric mean, 几何平均数/ j3 M4 k+ `2 P$ P* F
Gini's mean difference, 基尼均差
3 h2 j7 n# Z* K" o# l. q' g9 uGLM (General liner models), 一般线性模型
$ M7 `" c" P1 b9 [6 TGoodness of fit, 拟和优度/配合度1 Z6 `% x) c( w; j U
Gradient of determinant, 行列式的梯度4 b6 Q! r1 K) O. X
Graeco-Latin square, 希腊拉丁方. k& O% a* Y" X$ X0 ]4 Y
Grand mean, 总均值
t6 ^; s) g( `Gross errors, 重大错误
* F) t! Q: b8 kGross-error sensitivity, 大错敏感度$ C$ T5 o2 F5 S6 E4 |
Group averages, 分组平均/ ?5 Q; Q' E% q/ G4 a9 [3 _6 P
Grouped data, 分组资料
4 X; i w# Y8 p# g# H6 [( O! BGuessed mean, 假定平均数/ F7 e: |( M V) Q- v
Half-life, 半衰期
/ w* Z" K8 s0 iHampel M-estimators, 汉佩尔M估计量
- E# d( F/ L3 ^- `Happenstance, 偶然事件4 t4 [ x2 |/ d1 j
Harmonic mean, 调和均数8 u7 Y9 W6 Y$ L
Hazard function, 风险均数7 \) a- i5 w/ `6 |1 {' Z
Hazard rate, 风险率% r5 w0 H; i1 _3 a! a W% R
Heading, 标目
, X8 A7 Z k7 F! g8 [Heavy-tailed distribution, 重尾分布5 J; c [# k i, f# Z- z$ R2 M
Hessian array, 海森立体阵
" }# U/ b: T( c/ j) Q5 j3 ?5 j. NHeterogeneity, 不同质
# K4 q( \& T9 Y( c3 S K4 X2 bHeterogeneity of variance, 方差不齐
, k, X5 s2 H1 Q0 u5 a' eHierarchical classification, 组内分组9 c9 u/ h) d, Z- i2 ^
Hierarchical clustering method, 系统聚类法5 }% u0 D* ~0 l7 g
High-leverage point, 高杠杆率点% u$ H/ \' ?2 F% h1 S
HILOGLINEAR, 多维列联表的层次对数线性模型- e) e9 g2 g3 ^4 g" H! |" \
Hinge, 折叶点
* b1 n5 ~; n2 E |9 O2 hHistogram, 直方图
, J' [# g7 r/ b* b5 fHistorical cohort study, 历史性队列研究 6 J! y% M) k w1 L
Holes, 空洞
+ x$ O7 g! N8 \3 d7 L- D9 JHOMALS, 多重响应分析8 \8 s0 M4 Q* t, g% m2 o
Homogeneity of variance, 方差齐性
4 X. Z; B% W% N0 Z' E. N0 f( Z4 hHomogeneity test, 齐性检验
8 ` u. H; a0 O8 _; SHuber M-estimators, 休伯M估计量
; y" N( ]5 Y! |( ~Hyperbola, 双曲线
0 Z* }* S+ R. [2 J. RHypothesis testing, 假设检验0 r& A, q( I" Y; f8 f, N
Hypothetical universe, 假设总体0 y9 p, w& n1 H0 H' O) y
Impossible event, 不可能事件
2 s g( L. r% z* LIndependence, 独立性
4 `0 L- a9 }5 e& U1 P$ X4 ^Independent variable, 自变量
* x# t* X. |$ Z8 S, z; tIndex, 指标/指数8 k3 M' b9 x/ y$ o
Indirect standardization, 间接标准化法
) g% ^ A7 y6 b, J# [. ^; VIndividual, 个体8 T& X0 C: b3 v: D6 }$ [
Inference band, 推断带$ Q' G9 f$ V- R0 f$ r8 ^
Infinite population, 无限总体
c/ o! `" x* r% @! Z0 GInfinitely great, 无穷大
$ _0 [+ b* m" ?! z0 \Infinitely small, 无穷小
6 W# N2 e, Q, d; z9 uInfluence curve, 影响曲线) T, I7 H( {. \& f: s' b; q. k7 h
Information capacity, 信息容量3 j) j6 G6 [7 }" P- }
Initial condition, 初始条件8 e- a4 [9 I& ^
Initial estimate, 初始估计值0 L O8 r0 l4 h. \6 J6 W9 z5 r$ Z0 B& {
Initial level, 最初水平
- G6 M3 c! _+ E1 E/ K: H0 `$ P" i8 r8 S/ JInteraction, 交互作用; X- p- ]1 A4 ]# E
Interaction terms, 交互作用项
4 a" |# F @0 }" c) B( NIntercept, 截距
/ T, s. V1 I2 u4 v5 V4 Y) h" `Interpolation, 内插法- G) m) g( r$ h% E
Interquartile range, 四分位距8 H% ~+ S2 {: R2 r& j% c
Interval estimation, 区间估计
# Z* ]6 E3 v$ I! r3 w$ B' V& qIntervals of equal probability, 等概率区间
* _; W; l9 h# {' N# GIntrinsic curvature, 固有曲率7 q6 V1 k6 ~! p9 c2 _' T+ H( L, n
Invariance, 不变性
- j/ q5 s$ q zInverse matrix, 逆矩阵/ V9 d6 g k6 n2 ?4 ^# o
Inverse probability, 逆概率: A0 J+ `, D! N1 M2 p, i! R
Inverse sine transformation, 反正弦变换
* H3 E' S3 r ]6 h& G! k+ tIteration, 迭代
9 z' B* Y% b A- }Jacobian determinant, 雅可比行列式
9 U2 o6 a5 F+ H1 n; f6 iJoint distribution function, 分布函数2 z5 A' q6 }4 U' P2 c
Joint probability, 联合概率
) i2 G$ |* {- y2 e6 _$ [4 |Joint probability distribution, 联合概率分布
9 P1 `; @+ M* mK means method, 逐步聚类法
8 m7 G! Z* d: E$ m) m" OKaplan-Meier, 评估事件的时间长度 / V+ {$ T* a7 ^& T* ^& ^( A
Kaplan-Merier chart, Kaplan-Merier图4 B `/ ^3 ^3 Q7 U- b
Kendall's rank correlation, Kendall等级相关# l5 H8 V3 S0 r( ]* W; q
Kinetic, 动力学 a- B% Z: v0 x# j* j
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
. g# L9 [+ v4 o. X1 a8 U, OKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验& D5 {# ^: A8 [ S* e) r+ `
Kurtosis, 峰度 U d4 Y; R7 }9 r3 z1 J9 M
Lack of fit, 失拟
$ u' l8 N+ R3 z" G+ W4 `. Q5 \Ladder of powers, 幂阶梯
0 e, M7 H. e, ~9 x% GLag, 滞后# c) X- H+ b/ W* J( r
Large sample, 大样本
' }0 L0 K* f, b! U/ v8 wLarge sample test, 大样本检验
0 x# C0 y# }5 |# x! aLatin square, 拉丁方
! {; [% e. R \4 |! x7 K. ?. zLatin square design, 拉丁方设计2 D$ x& Q( C) b, h
Leakage, 泄漏$ |- b* ]3 Z7 W! O7 }! ~: y
Least favorable configuration, 最不利构形9 t: J% T7 e9 n: U/ n& L
Least favorable distribution, 最不利分布
# e9 N# s$ O7 l* ]8 f3 vLeast significant difference, 最小显著差法: E5 s8 e; I& O5 h
Least square method, 最小二乘法) D0 R9 k" G# c) m" p9 }6 k
Least-absolute-residuals estimates, 最小绝对残差估计
% e8 B( d$ t+ J( rLeast-absolute-residuals fit, 最小绝对残差拟合" b. W; N n- ?) S
Least-absolute-residuals line, 最小绝对残差线& y' ~& ^3 T u' m& I
Legend, 图例/ _' @9 W* Q, V* V! U2 W" |# ~
L-estimator, L估计量
# i* j& v9 @5 r4 c; Z: F& hL-estimator of location, 位置L估计量
9 f& V; r. U/ vL-estimator of scale, 尺度L估计量, ?; k6 g' G$ Q- A6 y
Level, 水平% p [( ^ B8 l' a+ K
Life expectance, 预期期望寿命+ U5 M( t! ?, c" x( F
Life table, 寿命表
* f: q$ ]6 P4 Y: T$ p& O. k; SLife table method, 生命表法
/ a ~5 l# U6 r8 \Light-tailed distribution, 轻尾分布
; b3 m& i$ K9 o7 i" ]6 |Likelihood function, 似然函数" a$ y$ J4 O0 m2 { F- n
Likelihood ratio, 似然比* [- j- [/ f8 b! {! M
line graph, 线图" b$ A/ F: |- }4 g
Linear correlation, 直线相关
3 v1 c- e+ }$ C+ ?1 iLinear equation, 线性方程
3 f7 t' @# [9 G$ d& M# _' l8 C7 LLinear programming, 线性规划2 h% u4 e$ N$ T* j: _' l# Y* m
Linear regression, 直线回归- b9 c* }1 n( F& F1 J2 U8 ]
Linear Regression, 线性回归 ]; P( l& d( f& Y3 [0 f; M0 g" j& k! K' O
Linear trend, 线性趋势
6 \* Y# h5 U8 _( X( f2 fLoading, 载荷
0 ?; O1 b* Z# [' vLocation and scale equivariance, 位置尺度同变性1 V0 ~, V' A( G
Location equivariance, 位置同变性6 c7 w9 q* V: G* @ k& a+ w; }
Location invariance, 位置不变性' k; k5 H* j; N& \) t) k
Location scale family, 位置尺度族
9 x9 K+ b" \) cLog rank test, 时序检验
9 A( c; w' L# y: G6 @/ tLogarithmic curve, 对数曲线
. t' f* z3 k9 F/ w& XLogarithmic normal distribution, 对数正态分布# ^8 p# E: ?' D: @0 `
Logarithmic scale, 对数尺度 H9 r* F6 W. ?+ V* C9 L
Logarithmic transformation, 对数变换
. i( n: U0 L; B/ y7 dLogic check, 逻辑检查
, E2 t, [+ p4 lLogistic distribution, 逻辑斯特分布/ z% X7 J/ |0 x# d. ^2 n9 y
Logit transformation, Logit转换6 M3 D. d$ H5 Q' A& A6 y0 x3 [
LOGLINEAR, 多维列联表通用模型 4 i! Z% O$ F' _/ a) T4 O5 w
Lognormal distribution, 对数正态分布
$ F0 n% t( n _& Y( w$ TLost function, 损失函数% W: g1 W9 X. H- O3 \5 E0 R2 e
Low correlation, 低度相关$ G3 Y+ K+ @4 o2 K5 w3 \
Lower limit, 下限4 ~; A! O8 a) Y- ~2 y5 B% r
Lowest-attained variance, 最小可达方差
* o7 ?/ P# ^2 C# q8 K! x# JLSD, 最小显著差法的简称
0 d1 i. B! x8 \3 ?5 bLurking variable, 潜在变量
, N( z& ]; J6 ]% Q" B7 q) vMain effect, 主效应, F( L7 c8 n9 \7 s5 {
Major heading, 主辞标目' s% ?& Q+ w* O5 S( A7 ]& P8 w
Marginal density function, 边缘密度函数
) V# ?. H" }$ m) J9 F) ~Marginal probability, 边缘概率' A, |# b1 g+ N+ ^
Marginal probability distribution, 边缘概率分布
+ }' S, [, U" k6 |Matched data, 配对资料
2 a+ m L7 ~$ ]4 JMatched distribution, 匹配过分布$ I# d `% Q! {4 m
Matching of distribution, 分布的匹配
% }) n( w* J; uMatching of transformation, 变换的匹配
9 }1 B/ m4 a# g" l& SMathematical expectation, 数学期望
2 p9 v# Q/ n1 \7 }) TMathematical model, 数学模型
' c! w/ u2 T5 _! i+ R9 E; J) sMaximum L-estimator, 极大极小L 估计量: w' p! d. C9 e! _4 r! S1 m
Maximum likelihood method, 最大似然法
; D. O! h" m6 L' c! R- u# x4 [1 wMean, 均数" s& B/ b D. Z3 p$ j
Mean squares between groups, 组间均方
9 ] S- r( ?, r/ OMean squares within group, 组内均方
7 ]2 X1 p/ M/ q/ FMeans (Compare means), 均值-均值比较% k; x% |4 R, ~/ Z) {) ~" J1 ?- y
Median, 中位数
+ I$ A: H& u/ d" }Median effective dose, 半数效量
* S0 S! n& K+ P& `Median lethal dose, 半数致死量5 X! k, D- u7 K' H! H1 N8 b. L
Median polish, 中位数平滑! U8 ^/ S9 B) @- A1 G- f. J
Median test, 中位数检验
8 s( E* Y: B/ r* M) ~ GMinimal sufficient statistic, 最小充分统计量
' D9 T- A8 [# ^! S) V+ a( y8 [Minimum distance estimation, 最小距离估计. X% C7 T0 @& J7 \# r& v
Minimum effective dose, 最小有效量
" T' y" M3 ]. f0 g/ A2 I( q2 oMinimum lethal dose, 最小致死量 D6 N1 x q- r- e& r+ C
Minimum variance estimator, 最小方差估计量 Q) u+ S5 K) q7 N% p+ U
MINITAB, 统计软件包/ W0 x+ z N5 i5 U
Minor heading, 宾词标目
( W2 }3 D4 c6 V3 UMissing data, 缺失值- T& ^3 Q" M) L9 W$ E- K7 C6 t$ a9 ]
Model specification, 模型的确定/ D. r0 a" _* m9 @! E$ \
Modeling Statistics , 模型统计- j9 Z' W: s4 v6 s
Models for outliers, 离群值模型& _$ l7 X* X8 B6 A
Modifying the model, 模型的修正
% m7 p) d+ j2 \: s5 M. DModulus of continuity, 连续性模
- ^8 C* P, L+ J: a& U: V1 B. IMorbidity, 发病率 ' d% l, n t. V0 ?6 }' F, ^: X3 o
Most favorable configuration, 最有利构形' B$ u3 I3 ]5 P4 S$ X. B: o# d
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
3 }7 W4 r. X+ v2 o' v) tMultinomial Logistic Regression , 多项逻辑斯蒂回归, w) f9 a! ~& S# \( e# `1 t
Multiple comparison, 多重比较
& |3 m4 x2 Z' Z4 i8 Z' i2 YMultiple correlation , 复相关
* u% L1 w/ M5 y: kMultiple covariance, 多元协方差/ y+ A; t# [& U6 g
Multiple linear regression, 多元线性回归
9 W- q2 ~5 L V2 Z* x4 Z2 J, xMultiple response , 多重选项
2 P" i5 ^0 B ]5 zMultiple solutions, 多解6 w0 z: g* c5 | b( G' x$ Y; b
Multiplication theorem, 乘法定理7 R0 }& x' w8 A& P% G
Multiresponse, 多元响应' E* {$ V' q& K0 l! P& d
Multi-stage sampling, 多阶段抽样* E9 J+ ^ G0 ]! Z* O& T4 \
Multivariate T distribution, 多元T分布
2 Y2 E2 E" j D; T2 x. K- NMutual exclusive, 互不相容3 C9 @! J7 M _
Mutual independence, 互相独立
9 F6 j! k0 u; Z# GNatural boundary, 自然边界
6 ]7 [! m; @' K) y! C$ C* W) |7 DNatural dead, 自然死亡
+ S9 |" v, U1 I0 ~) m8 r1 |5 V: ENatural zero, 自然零
$ q6 e9 W" h9 [6 @4 u8 O: u4 |Negative correlation, 负相关. {; K+ B9 K+ T5 Z- L" \7 Q
Negative linear correlation, 负线性相关- \0 A9 b2 o4 G+ Y$ f! d
Negatively skewed, 负偏
7 e# Y# n! D5 j- \) Y0 v0 _& cNewman-Keuls method, q检验5 K: J9 s+ N. C
NK method, q检验& z! `8 I' M: @: C7 ~
No statistical significance, 无统计意义
: T3 Y! L* n, G Q7 ^Nominal variable, 名义变量
- d3 h8 B4 A d5 x8 m0 |Nonconstancy of variability, 变异的非定常性
- u# R3 c0 b2 C$ pNonlinear regression, 非线性相关
# V- T& n: Y; zNonparametric statistics, 非参数统计( G% |0 @% {: P) r
Nonparametric test, 非参数检验, C8 V9 q4 }1 ~6 l+ M7 o& s) Q
Nonparametric tests, 非参数检验, t; `) M, \/ H: S, |- _! e! i
Normal deviate, 正态离差5 s* ?1 h' J$ O0 {
Normal distribution, 正态分布: S9 Q' y1 s( F+ b% \
Normal equation, 正规方程组
1 H6 Q9 |9 B4 U$ K/ QNormal ranges, 正常范围0 K6 y! Y% J! s! U- x
Normal value, 正常值" b4 V( l4 T; q i
Nuisance parameter, 多余参数/讨厌参数
7 n7 V+ }4 D/ X6 p+ t& e) VNull hypothesis, 无效假设
( a9 N" p( p# a2 G% g, c. aNumerical variable, 数值变量
; E+ g, D( Q4 n2 TObjective function, 目标函数
5 h/ |" H$ e P! d8 c% V1 V* @Observation unit, 观察单位4 n. A3 l2 e& l
Observed value, 观察值) V G/ j7 u1 H$ l
One sided test, 单侧检验1 \& ]6 Z& _7 R) x
One-way analysis of variance, 单因素方差分析
! b, ~, r/ B0 T/ ?2 v+ P7 @) QOneway ANOVA , 单因素方差分析
: r2 S$ q/ D) v( fOpen sequential trial, 开放型序贯设计
- m# @. `2 t$ Z+ Z ]: {8 C0 FOptrim, 优切尾: \! K& X) u( A6 @) ]
Optrim efficiency, 优切尾效率
/ Z% |& Q6 o- k: E9 FOrder statistics, 顺序统计量
6 O& ^2 T- G. K, }' POrdered categories, 有序分类 c7 C& b! f$ O$ Y9 c! q
Ordinal logistic regression , 序数逻辑斯蒂回归
2 T% n) X6 b$ K1 L+ uOrdinal variable, 有序变量
+ P0 \: O+ H& k; hOrthogonal basis, 正交基1 t' H [+ Z; l: f& Q1 n
Orthogonal design, 正交试验设计
" i# a: S4 d1 ^' x4 k! k9 dOrthogonality conditions, 正交条件
! \7 c* M- w( m( l6 o; q/ cORTHOPLAN, 正交设计 ' A& T8 h& _; G
Outlier cutoffs, 离群值截断点& k. O9 X0 i& U y z. r5 `1 [
Outliers, 极端值. P, J& g" K) l, w. W+ S& D. ~) }3 p
OVERALS , 多组变量的非线性正规相关
1 A$ X: ]: ~& NOvershoot, 迭代过度( d/ P8 D5 P( W ~1 P, r9 K
Paired design, 配对设计* P+ t$ L. W9 A' Z1 B M( ~5 o& \
Paired sample, 配对样本
- j% ~& h+ F- ]8 RPairwise slopes, 成对斜率
1 z P' j; r" Z& s7 d/ _ ^( z* SParabola, 抛物线
* p% D4 t2 ?: J& R) q( P L; H5 E0 }; sParallel tests, 平行试验
" b9 U* @5 [6 X( o1 aParameter, 参数
: b9 ~) o% |5 o+ J1 wParametric statistics, 参数统计
9 v3 ^) I) Y- b) SParametric test, 参数检验
2 l. ^" Y& l! P, V1 [Partial correlation, 偏相关
8 C' b2 h2 ]4 E* v1 BPartial regression, 偏回归; ?" e& Y' T) K1 ~0 v
Partial sorting, 偏排序" Q( D, Q6 j$ u
Partials residuals, 偏残差
5 Y0 K8 @' V- wPattern, 模式
' B. a0 e& n H0 p$ A/ pPearson curves, 皮尔逊曲线
. H6 ^' U f- L) @) l8 HPeeling, 退层 J5 }0 E# B2 a5 [( e
Percent bar graph, 百分条形图
/ L/ ^% Y- J* v4 OPercentage, 百分比
0 {. I$ @" l+ w' p+ F( YPercentile, 百分位数) O. R+ H4 ?4 m+ z7 U0 l
Percentile curves, 百分位曲线
0 Q+ n: X3 B4 APeriodicity, 周期性
" P/ r K6 V+ d& [Permutation, 排列2 q) w, L3 H* H. i4 y. j: |2 K L) V
P-estimator, P估计量* i- p& E* A$ v/ i. e1 ]! b
Pie graph, 饼图9 c) I! ^- J- p) g4 Q3 M( B
Pitman estimator, 皮特曼估计量
. p0 @+ P' O4 \. n5 gPivot, 枢轴量9 Y' S7 E: l) }9 i- f& S
Planar, 平坦
& Z4 q9 U& L! p3 H+ EPlanar assumption, 平面的假设
4 C1 w0 F& c, k6 }# O; ]8 A' iPLANCARDS, 生成试验的计划卡: ]9 s) `4 Q8 S6 f, R. [ }, q: ]) R
Point estimation, 点估计# [% ]/ v3 C$ ^# {4 H! ]: I
Poisson distribution, 泊松分布
2 u8 w' G: m/ C6 S# \Polishing, 平滑 D7 y9 \" |8 p
Polled standard deviation, 合并标准差
8 q4 ~5 w8 |3 ?: B6 WPolled variance, 合并方差
5 g- u1 u/ m8 zPolygon, 多边图
# S# g) l! }9 k APolynomial, 多项式
, C I* E- E6 c+ t1 @1 R3 {" zPolynomial curve, 多项式曲线
$ q8 O" b) d9 ?& bPopulation, 总体
; _) {; f' W- s9 W/ z! oPopulation attributable risk, 人群归因危险度1 i- D t: O# h. F3 {+ ~/ O d$ k
Positive correlation, 正相关, ]+ q/ I. \1 V& {" D0 R" d% E
Positively skewed, 正偏: Q7 p& W# E2 P% U8 ^1 q
Posterior distribution, 后验分布
6 a' [* }! P9 d. APower of a test, 检验效能
, w* e% `6 G" o% rPrecision, 精密度3 \; j0 p3 k7 d z
Predicted value, 预测值, @ m; R3 B) e6 c
Preliminary analysis, 预备性分析2 A$ \" }8 ?* U k% R8 {
Principal component analysis, 主成分分析8 U2 o, V+ W" B5 z4 {
Prior distribution, 先验分布) X3 F: _& l, e' O( v+ Z
Prior probability, 先验概率9 H) q, {% l |) l# h" x: k
Probabilistic model, 概率模型' s2 X# r0 c" X; H
probability, 概率
) z& G- \& o- R2 GProbability density, 概率密度
5 c8 N( { t2 [* G kProduct moment, 乘积矩/协方差) ?1 Y+ m" b- O1 {
Profile trace, 截面迹图4 f& [2 [) v9 D+ ~) x
Proportion, 比/构成比
) _; f o! o( D8 ^0 QProportion allocation in stratified random sampling, 按比例分层随机抽样( Z! a: {& j9 z% K* d3 j$ H' b4 b
Proportionate, 成比例% P- V/ M; b5 `( Q3 A) `
Proportionate sub-class numbers, 成比例次级组含量
6 q2 q. G' @0 Q5 V4 c; A$ lProspective study, 前瞻性调查. o0 v7 T' C& C- X
Proximities, 亲近性 1 b; }9 J0 @& }3 G, Q3 Y- `) |
Pseudo F test, 近似F检验2 C7 p. T! G) ?! K
Pseudo model, 近似模型1 b3 o. U1 z# Q/ s; y) o) H
Pseudosigma, 伪标准差
( R+ W1 l; s. A* `7 L: z! V' C7 rPurposive sampling, 有目的抽样+ y I$ Z1 O- `7 X; U3 q
QR decomposition, QR分解+ x+ Q; n. I, C f" P( H' V. q% `
Quadratic approximation, 二次近似- q! X4 N! q0 p* k
Qualitative classification, 属性分类, x/ k0 n1 w5 R
Qualitative method, 定性方法
6 K# `2 `/ W$ [8 f. r+ hQuantile-quantile plot, 分位数-分位数图/Q-Q图5 g R2 ]& Y! c$ r# _8 i
Quantitative analysis, 定量分析/ F5 w5 k" [* k$ F( |8 b! h7 ^6 `9 @
Quartile, 四分位数
8 u- n$ X6 T( L- }$ `7 @5 h# S# mQuick Cluster, 快速聚类
2 u$ P! Y/ @9 b. p, P7 jRadix sort, 基数排序
/ N* U1 m: G# |" U! }- ?Random allocation, 随机化分组
9 e* K6 v: G8 g! @) i, c8 SRandom blocks design, 随机区组设计
$ S3 c+ O' V$ IRandom event, 随机事件! j% X! s" h0 Z: e1 P5 L' ?; Q$ C- ]
Randomization, 随机化! w" i/ {+ t' P7 R6 P, ]3 ~1 o
Range, 极差/全距
/ t" j7 a6 M, V nRank correlation, 等级相关* J4 y# Y5 z+ X
Rank sum test, 秩和检验3 l' m0 Q* `7 t+ K1 R6 |7 [
Rank test, 秩检验
. x4 r. \ `" n$ z- ]Ranked data, 等级资料
& Y ]) T* D6 ]' m9 KRate, 比率, l) ~7 @0 x5 h: f+ F) x
Ratio, 比例# C% T* ?5 u8 i$ g- o4 b+ n
Raw data, 原始资料! F# j, o) N o8 w3 Q
Raw residual, 原始残差
# O4 e9 k/ }4 V% _; u2 DRayleigh's test, 雷氏检验
" d' E" J$ ^9 T$ g' SRayleigh's Z, 雷氏Z值 ( i$ w/ C& _+ }- i- D3 Q% k) s2 \- V
Reciprocal, 倒数
/ r1 b6 G5 D e- G' MReciprocal transformation, 倒数变换
% J& r; {* X& p7 w- q# x! HRecording, 记录
( B- _7 Z0 Y$ q/ T- XRedescending estimators, 回降估计量
) S4 Y) V7 R" m; C/ S$ u; PReducing dimensions, 降维7 }" d5 @) q# w6 \
Re-expression, 重新表达8 E: ^+ }0 O( ^: _8 S8 ]" k* e
Reference set, 标准组# R u, J0 ^0 ]' [1 x; a3 e, p
Region of acceptance, 接受域7 w& e( u0 \6 O) y8 {7 H
Regression coefficient, 回归系数
& u( G0 k7 V/ S5 qRegression sum of square, 回归平方和9 @2 M. z7 n$ g
Rejection point, 拒绝点& F8 z& G, @* M
Relative dispersion, 相对离散度4 \. Z) m9 N" J& ]
Relative number, 相对数- X' z3 I ?$ B% p- _' w9 \+ Q
Reliability, 可靠性
# F7 O5 |' ]8 P' p; `2 yReparametrization, 重新设置参数! F9 M( b' ^8 M* Z, T) t/ I
Replication, 重复
, k! |0 F( z% d8 J& eReport Summaries, 报告摘要/ u& {: F9 ?9 b1 J% s
Residual sum of square, 剩余平方和$ T# f" t4 L6 m2 d# A9 N! _9 D
Resistance, 耐抗性
8 J K# z; B* n; yResistant line, 耐抗线$ |, W! k# i6 x+ U: W/ f
Resistant technique, 耐抗技术/ `0 ~. g& R& t+ y" r7 B, d6 y
R-estimator of location, 位置R估计量, i" b; R; ^& U+ |
R-estimator of scale, 尺度R估计量1 l$ |( X- M( m8 G. ]: K
Retrospective study, 回顾性调查( [+ J+ S! i X. q- h# v# H
Ridge trace, 岭迹
! g4 c8 K! w% j/ x/ TRidit analysis, Ridit分析
# F. M2 f5 B6 s7 f7 _Rotation, 旋转6 \4 x! Q% @8 W) Z4 M' u; Y
Rounding, 舍入! o/ o$ D( ^/ |. n' H5 r; Z
Row, 行
: |2 A$ x5 ?' iRow effects, 行效应
0 P; N4 I: o8 n/ K b+ wRow factor, 行因素2 H% e% S$ h4 ?) k
RXC table, RXC表
4 L5 {+ m9 D# g4 oSample, 样本+ V8 R0 L+ ~0 P% @% Y, U
Sample regression coefficient, 样本回归系数
2 g, V$ Z9 O* _ L. y0 YSample size, 样本量# k+ o6 a( y) W9 [- M
Sample standard deviation, 样本标准差& ~1 f1 R, A" ]! _& h3 z
Sampling error, 抽样误差9 F& G* Y6 s! C d6 V+ |$ b
SAS(Statistical analysis system ), SAS统计软件包* ~. l# J) y/ |/ t. X9 b/ i4 }
Scale, 尺度/量表
0 Q' i' l% ^) W3 y: R. Q. n& T6 kScatter diagram, 散点图
7 H% m$ s5 [( g2 h& ZSchematic plot, 示意图/简图" e5 K/ e4 w& L) Q% Q
Score test, 计分检验# z% S% s! s% P# y
Screening, 筛检& x5 z' O, {/ T5 c' [4 n- F
SEASON, 季节分析
3 q( N. A) J0 c7 P6 ~! g4 y( pSecond derivative, 二阶导数
* I$ @1 P7 M7 X* ]7 P% t0 HSecond principal component, 第二主成分
. p9 i% R4 A# {) U1 `# L( ySEM (Structural equation modeling), 结构化方程模型
7 f# ~; \& D+ E- O( Y$ VSemi-logarithmic graph, 半对数图, w1 v, c! X0 L) g
Semi-logarithmic paper, 半对数格纸
; _8 h8 q+ E* Q- t9 p, DSensitivity curve, 敏感度曲线" N5 l8 ?+ Z3 B
Sequential analysis, 贯序分析2 `& |9 l8 B+ |) T
Sequential data set, 顺序数据集
) S7 I; a5 }9 xSequential design, 贯序设计
1 W. `9 K+ L3 s$ W; a! i8 USequential method, 贯序法7 p3 s* Z5 }9 i& }1 G f. E
Sequential test, 贯序检验法. a/ n# q! C' k. l
Serial tests, 系列试验
) E+ I4 T/ e W4 t' S1 h' C% cShort-cut method, 简捷法 7 t7 z7 w: z6 l' r9 {/ Y+ W, |
Sigmoid curve, S形曲线
+ g7 j3 N" y7 c. q5 r& f; WSign function, 正负号函数- M4 h& b! m j
Sign test, 符号检验
8 {) E( V, H; H2 g" fSigned rank, 符号秩
) t2 ~! F" X$ L* t `4 Q$ ^2 ZSignificance test, 显著性检验
! \. u5 n! A# D4 FSignificant figure, 有效数字) j9 r% E6 B1 t4 M
Simple cluster sampling, 简单整群抽样1 ?) y+ a+ ~1 [& S+ |5 V, d# J
Simple correlation, 简单相关
0 N- r# B! p8 K) r' bSimple random sampling, 简单随机抽样
( K* [/ s5 z* L# i" s# R# HSimple regression, 简单回归
8 Q1 ?/ B( I5 usimple table, 简单表. a4 |* s) k1 p
Sine estimator, 正弦估计量! a8 ?0 K+ O& g1 F/ L3 N% T
Single-valued estimate, 单值估计
! b& q6 z) h+ B9 {/ j1 g5 K- T, U. [Singular matrix, 奇异矩阵
) X& `4 v# K, G4 Z# }Skewed distribution, 偏斜分布! l* ?3 a [) Q0 J' K
Skewness, 偏度0 L7 d! \6 U0 i6 A5 w
Slash distribution, 斜线分布/ E/ V1 x* E& a! N
Slope, 斜率
) U1 q2 f" f- F* W8 ]Smirnov test, 斯米尔诺夫检验$ R, m5 ?- i* C3 y, Z% |1 N
Source of variation, 变异来源' w# m3 Y& O% T: a* O% d
Spearman rank correlation, 斯皮尔曼等级相关
( U# Y- c, F* R( jSpecific factor, 特殊因子
4 o$ T, ~$ N+ k) NSpecific factor variance, 特殊因子方差
" D& c6 r. j x0 P$ {" SSpectra , 频谱
2 S- x x, s/ T6 Q F) lSpherical distribution, 球型正态分布
) s- L u+ |% }9 a) v( [Spread, 展布9 t5 j+ A! ?8 P- S" B
SPSS(Statistical package for the social science), SPSS统计软件包
( S% J# i* ]0 H& L5 w; s3 r# hSpurious correlation, 假性相关
L) G' q' o R0 }+ \Square root transformation, 平方根变换+ S8 U) B6 k" E- y
Stabilizing variance, 稳定方差- o7 R$ c9 s/ J9 m8 _
Standard deviation, 标准差
3 u$ @) e2 R6 B( \( x' U# g+ RStandard error, 标准误9 b% _$ M5 n/ y R
Standard error of difference, 差别的标准误
+ n# _, p! f9 }Standard error of estimate, 标准估计误差
* y: u% n* T+ c/ Z! _% L! ?Standard error of rate, 率的标准误
" {6 g. Q$ _0 z& ?Standard normal distribution, 标准正态分布( o! y& D6 D; }9 J
Standardization, 标准化) C7 @- t3 H' W( l% U7 k5 `
Starting value, 起始值
" L. H# f& P. KStatistic, 统计量
1 }7 z$ f; }* |3 r; b* @; S6 wStatistical control, 统计控制& h8 v6 r$ d. x' _9 G; D) e
Statistical graph, 统计图, z: i5 ]) f# d4 z6 {5 x8 C
Statistical inference, 统计推断# a0 }: \1 G1 K m; g5 e8 c6 @
Statistical table, 统计表5 B n' j2 ?7 \8 u! b. T* o
Steepest descent, 最速下降法1 e; Q" F' \: L/ B2 ~1 }9 t
Stem and leaf display, 茎叶图
9 s3 m, [1 s' AStep factor, 步长因子
& M2 M# x0 I7 H( P! H" W% W& R7 J5 ~Stepwise regression, 逐步回归, L8 K- U( ~3 Q9 P d) k
Storage, 存
+ ]! A/ V2 t+ A7 k" l9 w3 T. {Strata, 层（复数）
z6 L% o5 d4 I L1 UStratified sampling, 分层抽样 h: z' b4 f* C
Stratified sampling, 分层抽样
# J! ^4 i8 K$ R% B8 y/ sStrength, 强度" W3 Z1 M/ ^7 Y- G; n
Stringency, 严密性
- \/ K0 {& u4 b9 WStructural relationship, 结构关系) o+ [8 }$ g* Z A
Studentized residual, 学生化残差/t化残差
5 _! f" g" u) j c% [$ P: q; N+ lSub-class numbers, 次级组含量9 E8 ]/ U. E1 c5 q+ W
Subdividing, 分割
0 c2 Z/ S4 M) jSufficient statistic, 充分统计量' Y2 o0 t& |) N5 D: b6 q7 ?: z
Sum of products, 积和
% h/ G, Q6 C) X$ s- n- ]# ~4 a8 G$ tSum of squares, 离差平方和
+ r, z3 r3 D6 }2 u; P7 RSum of squares about regression, 回归平方和
" T3 s% a3 j7 u# q9 D2 X1 oSum of squares between groups, 组间平方和% _# x' m; o1 ^6 v5 `' P' ?; K
Sum of squares of partial regression, 偏回归平方和
7 u# C' v6 x1 d# tSure event, 必然事件- T$ @9 t' b* h; `% N4 t: E+ i, b
Survey, 调查0 @. m# J j- o( C
Survival, 生存分析
6 {4 n h# Q7 m- w( H$ C# s2 ESurvival rate, 生存率
+ j1 a7 Q' _) P1 R7 K0 jSuspended root gram, 悬吊根图
* ]4 m* l) N5 C, v& ySymmetry, 对称- f; I2 G- w' g! R
Systematic error, 系统误差
3 w$ a1 G3 l: P4 U8 h+ nSystematic sampling, 系统抽样
0 I4 K7 c, `2 H5 Q% s1 ZTags, 标签% q/ a1 ]3 i6 h% N$ k- O7 O
Tail area, 尾部面积8 I8 v$ D, E- g2 S# p0 i" T+ A
Tail length, 尾长
% z8 X4 A* k; M9 }' P5 e# HTail weight, 尾重, J$ L s' |% v, i% K3 H! E' O( X
Tangent line, 切线& p" O% b+ X; h( g
Target distribution, 目标分布. ]+ y, U! ~% T w4 T4 }. |9 b
Taylor series, 泰勒级数
6 d4 h% z4 W6 x) U( l0 QTendency of dispersion, 离散趋势
+ [, ]) o1 F! M0 \8 C9 k. bTesting of hypotheses, 假设检验
8 S0 g/ }1 v( `% K9 e4 N/ U( G1 @Theoretical frequency, 理论频数; M8 m7 U0 c( Z: t( a) _% @
Time series, 时间序列; Y/ ~6 y1 \/ {+ X$ `2 j+ D
Tolerance interval, 容忍区间0 g7 D. K4 m1 I
Tolerance lower limit, 容忍下限: _7 W3 Z" J w
Tolerance upper limit, 容忍上限
: O+ |! l' W& Q3 mTorsion, 扰率5 P$ n: ?7 P* d: K
Total sum of square, 总平方和
' [( q% L8 c$ ~% STotal variation, 总变异0 }4 X( p! K0 ^* ?' l2 N$ l1 B
Transformation, 转换
$ ~& {4 w0 g. c3 j1 T8 aTreatment, 处理 I! B S/ B8 i9 y
Trend, 趋势0 d" B% g ]% ?2 M7 m9 G
Trend of percentage, 百分比趋势( b1 t- M; t3 @) w* k3 ]
Trial, 试验
9 y. y5 N. b% ?7 Z oTrial and error method, 试错法
; H6 k! w3 S1 Y( VTuning constant, 细调常数1 I" y7 G( N" P8 g7 g7 ^( p0 k
Two sided test, 双向检验1 z2 ^8 C0 R5 i) w
Two-stage least squares, 二阶最小平方
( S9 Z4 m2 _0 kTwo-stage sampling, 二阶段抽样
' W: C3 p4 d9 x) \1 z; B) X. D; }Two-tailed test, 双侧检验
! n- D) q9 y8 q7 k: u2 K7 m' i% VTwo-way analysis of variance, 双因素方差分析6 N. }0 Y# c4 R, e( \0 t: N' S6 }
Two-way table, 双向表
% L/ }& H1 ]+ P X7 n% IType I error, 一类错误/α错误
5 p w$ w6 n- w) N- f* u9 W/ {Type II error, 二类错误/β错误/ g3 v {2 _$ i" V. ~' \; u+ z
UMVU, 方差一致最小无偏估计简称$ ^$ D; I, c; |2 y5 W1 w
Unbiased estimate, 无偏估计& y5 J) A- S4 w' i
Unconstrained nonlinear regression , 无约束非线性回归
) u2 G: m& e# o8 _Unequal subclass number, 不等次级组含量
1 X7 p% d5 b& `4 o: a0 uUngrouped data, 不分组资料
b0 R/ @, A1 T- E4 S5 TUniform coordinate, 均匀坐标
- c; T- o1 X2 H4 t- I w9 AUniform distribution, 均匀分布2 H: k5 p0 ]* s. t9 g6 j
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
0 _/ }: E0 A- j8 q qUnit, 单元
0 t* Q' @7 i' D. `8 |8 @0 eUnordered categories, 无序分类
1 G" g; z: w' ?; l) a8 F/ g5 s- AUpper limit, 上限
; c, n( q; K4 D) L: QUpward rank, 升秩: c3 A$ f! I% q% A2 @3 o) T
Vague concept, 模糊概念, y9 u( O/ F4 j3 y# `* V! Z
Validity, 有效性 g/ Z0 s! Q! o
VARCOMP (Variance component estimation), 方差元素估计
$ _- _1 w5 N. y" q KVariability, 变异性
- l) T' \+ a1 Q5 i+ cVariable, 变量9 ~3 H. X8 F& t0 z2 [
Variance, 方差& I; c8 L2 K2 l/ y+ C8 D! `4 [* J
Variation, 变异. v0 l* m3 a3 M! T/ n1 Y7 h$ K
Varimax orthogonal rotation, 方差最大正交旋转
6 j- l! F/ R. I# u3 U+ a% wVolume of distribution, 容积
# {$ B# v; A. k! b- \5 jW test, W检验3 x! b: J; E' q2 X1 \5 q' M
Weibull distribution, 威布尔分布) k5 o% I4 g' S: Q! L8 n
Weight, 权数& E. p8 b/ X+ R6 n" G* g1 B' h" b" o
Weighted Chi-square test, 加权卡方检验/Cochran检验
+ W- g& N4 n4 l' _Weighted linear regression method, 加权直线回归
& {0 ]" p. c n; N' z$ q! v* @Weighted mean, 加权平均数
- i' I9 ^) u: \Weighted mean square, 加权平均方差
) l# c: U! f- R) ^- GWeighted sum of square, 加权平方和
9 H/ D) T/ Y! M! fWeighting coefficient, 权重系数* F, W! s9 l3 ]% k! Y
Weighting method, 加权法
7 M' D5 x- V2 k9 z5 VW-estimation, W估计量8 o) C! S- |* p1 [& J
W-estimation of location, 位置W估计量
% K: p. R" S) W, r% i+ U `- WWidth, 宽度" N+ |' o5 [/ }" ?
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验, O6 y( k3 l/ w
Wild point, 野点/狂点
, v2 y$ z4 F, cWild value, 野值/狂值
6 B4 R& N1 s6 H6 z9 SWinsorized mean, 缩尾均值
4 J$ T2 t$ W5 y$ ~( iWithdraw, 失访 ! e6 J0 n0 [! o
Youden's index, 尤登指数
) ?% r- e5 z" ?' E9 S; p7 OZ test, Z检验
3 [5 }1 E0 r8 r* V/ P) iZero correlation, 零相关
0 Y9 Q& _; }! S M* Y# Z: QZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
